Amwell CMO: Google partnership will focus on AI, machine learning to expand into new markets – FierceHealthcare

Amwell is looking to evolve virtual care beyond just imitating in-person care.

To do that, the telehealth companyexpects to use its latestpartnership with Google Cloud toenable it to tap into artificial intelligence and machine learning technologies to create a better healthcare experience, according to Peter Antall, M.D., Amwell's chief medical officer.

"We have a shared vision to advance universal access to care thats cost-effective. We have a shared vision to expand beyond our borders to look at other markets. Ultimately, its a strategic technology collaboration that were most interested in," Antall said of the company's partnership with the tech giant during a STATvirtual event Tuesday.

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"What we bring to the table is that we can help provide applications for those technologiesthat will have meaningful effects on consumers and providers," he said.

The use of AI and machine learning can improve bot-based interactions or decision support for providers, he said. The two companies also want to explore the use of natural language processing and automated translation to provide more "value to clients and consumers," he said.

Joining a rush of healthcare technology IPOs in 2020, Amwell went public in August, raising$742 million. Google Cloud and Amwell also announced amultiyear strategic partnership aimed at expanding access to virtual care, accompanied by a$100 million investmentfrom Google.

During an HLTH virtual event earlier this month, Google Cloud director of healthcare solutions Aashima Gupta said cloud and artificial intelligence will "revolutionize telemedicine as we know it."

RELATED:Amwell files to go public with $100M boost from Google

"There's a collective realization in the industry that the future will not look like the past," said Gupta during the HTLH panel.

During the STAT event, Antall said Amwellis putting a big focus onvirtual primary care, which has become an area of interest for health plans and employers.

"It seems to be the next big frontier. Weve been working on it for three years, and were very excited. So much of healthcare is ongoing chronic conditions and so much of the healthcare spend is taking care ofchronic conditionsandtaking care of those conditions in the right care setting and not in the emergency department," he said.

The companyworks with 55 health plans, which support over 36,000 employers and collectively represent more than 80million covered lives, as well as 150 of the nations largest health systems. To date, Amwell says it has powered over 5.6million telehealth visits for its clients, including more than 2.9million in the six months ended June 30, 2020.

Amwell is interested in interacting with patients beyond telehealth visits through what Antall called "nudges" and synchronous communication to encouragecompliance with healthy behaviors, he said.

RELATED:Amwell CEOs on the telehealth boom and why it will 'democratize' healthcare

It's an area where Livongo, recently acquired by Amwell competitor Teladoc,has become the category leader by using digital health tools to help with chronic condition management.

"Were moving into similar areas, but doing it in a slightly different matter interms of how we address ongoing continuity of care and how we address certain disease states and overall wellness," Antallsaid, in reference to Livongo's capabilities.

The telehealth company also wants to expand into home healthcare through the integration of telehealth and remote care devices.

Virtual care companies have been actively pursuing deals to build out their service and product lines as the use of telehealth soars. To this end, Amwell recently deepened its relationship with remote device company Tyto Care. Through the partnership, the TytoHome handheld examination device that allows patients to exam their heart, lungs, skin, ears, abdomen, and throat at home, is nowpaired withAmwells telehealth platform.

Looking forward, there is the potential for patients to getlab testing, diagnostic testing, and virtual visits with physicians all at home, Antall said.

"I think were going to see a real revolution in terms ofhow much more we can do in the home going forward," he said.

RELATED:Amwell's stock jumps on speculation of potential UnitedHealth deal: media report

Amwell also is exploring the use of televisions in the home to interact with patients, he said.

"We've done work with some partners and we're working toward a future where, if it's easier for you to click your remote and initiate a telehealth visit that way, thats one option. In some populations, particularly the elderly, a TV could serve as a remote patient device where a doctor or nurse could proactively 'ring the doorbell' on the TV and askto check on the patient," Antall said.

"Its video technology that'salready there in most homes, you just need a camera to go with it and a little bit of software.Its one part of our strategy to be available for the whole spectrum of care and be able to interact in a variety of ways," he said.

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June Launches Third Generation Oven with the Latest in Artificial Intelligence To Elevate and Enhance the At-Home Cooking Experience – PRNewswire

SAN FRANCISCO, Oct. 28, 2020 /PRNewswire/ --June, the cook-tech company, launches its third generation oven with updated hardware and software for the smartest cooking experience in the category. The 12-in-1 smart appliance can air fry, slow cook, grill, dehydrate, broil, bake, proof, stone fire pizza, roast, toast, keep foods warm and reheat with the skill of a chef and precision of a computer.

The June Oven is the world's first and only intelligent convection oven with a streamlined touchscreen interface and high performance camera inside that can identify hundreds of foods to start an automatic cook-program. With a rapid increase of at-home cooking, the third generation oven has been re-engineered to make the cooking experience easier and more seamless.

"This new world has created a lifestyle change for many, bringing people back into the kitchen to cook or learn to cook for themselves and loved ones," said Matt Van Horn, co-founder and CEO of June. "June is at the forefront of this culinary shift because we take the guesswork out of cooking with perfect results each time. We've seen a dramatic increase in usage and demand over the past year and we're excited to be back on the market with an upgraded model with even more functionality."

The latest software has been added to give users an even better cooking experience. Each of the six heating elements can now be controlled individually, as opposed to the second generation, which was controlled in three groups. This opens up endless cooking possibilities including rotisserie which allows for evenly roasted proteins and zone cooking which is enabled using the in-oven camera to detect where food is placed in the oven. June will focus the heating elements only in the area where food is to ensure a faster, better and more energy efficient cook session.

"The rise in at-home cooking has caused us to reevaluate June's cook-programs to achieve more culinary possibilities not captured by a standard home oven. With the new hardware and software updates on the third generation oven, we are able to introduce additional cook modes such as grilling and stone firing pizza increasing the June to a 12-in-1 appliance. The addition of the ability to control each individual heating element's timing and intensity allows June to create the perfectly roasted rotisserie chicken and other proteins," said Nikhil Bhogal, co-founder and CTO of June.

The new oven comes with a high quality aluminum handle that has a noticeable impact on a user's first touch impression. Guard rails on the top heating elements have been added along with new convection fan motors that reduce vibration and sound. A new chip set has also been implemented to improve connectivity.

The third generation will launch with three bundles to appeal to every customers' needs. They vary in price ranging from $599 to $999, depending on the quantity of accessories, including the newly launched Pizza and Grill Kit. Customers will be given the choice to pick from a variety of membership options, available in 2021, that will include additional remote control features, exclusive recipes, live videos and more all through the June app on their mobile device, available on the Apple App Store and Google Play Store.

All third generation ovens are available for presale on October 21. Visit juneoven.com to learn more about the different bundles and membership options.

About JuneJune, founded in 2013 by Matt Van Horn and Nikhil Bhogal, pioneered the smart oven with the world's first and only intelligent convection oven that functions as an all-in-one cooking appliance. Through innovative technology, elegant design and unprecedented performance, the June Oven makes cooking easy for everyone.

Media ContactFactory PREmail: [emailprotected]

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6 Ways to Improve your Business with Artificial Intelligence – ReadWrite

Artificial Intelligence is the technology that bestowed us with a fairytale-like functionality in our homes and offices. Have you seen the Beauty and the Beast movie? In that movie, the beauty was in the beasts castle, and there was no other living creature there. She was all alone, except she had a talking and moving clock, a candelabra, a teapot, and a teacup. Here are six ways to improve your business with artificial intelligence.

The wonderful technology that can make our lives easier is known as Artificial Intelligence and you can talk to it, too.

The simplest example of artificial intelligence is Alexa and Siri. Imagine calling someone when Siri was not there. You have to find their name in the contacts, and then you have to dial them up. Now, you can simply say, Hey Siri, call XYZ, and Siri will call them.

As technology is increasing, the demands of users are also increasing. It is becoming hard for businesses to keep up with those demands. If a business wants to grow, they have to come online. Having a business app or website is that you cannot just launch a website/app and not have online support. You have to track who visits your website/app, and you have to do something to convert that potential client into a real client.

But the thing here is that you or your support guy cannot be online 24*7. If a user comes midnight to shop or have an inquiry and message you, you have to reply within a minute or at most in 5 minutes, or else they will leave your site/app. This is a task that is not possible, but deep down, you know that this is a matter that does need to be solved.

In this case, conversational AI can be used that can trigger a reply once they come across a keyword. If they encounter something unknown, they can simply answer that please provide your email address or phone number, and the team will contact you as soon as possible. At least some reply is better than nothing.

Moreover, if you add enough keywords, the conversational AI can talk like a support person. Dish Network has tested this thing, and in their observation, customers rate interactions with virtual agents the same, and sometimes even better, in comparison to the human support staff.

When a machine does work, it is error-free. Moreover, if you let the machine do the job, you will get more time to do tasks that require human interaction. This way, you will enable yourself to do more important tasks and work productively. As a startup or a small business, this can be the competitive gain that you were looking for.

Lets have a look at how you can improve your business with Artificial Intelligence.

We have so many marketing ideas, but the main reason why many of them dont work is that we cannot target the right audience. As a content writer, I was writing a blog about cloud computing, and from that day, Google started showing me ads for cloud computing. I am not a buyer here, but as I searched for the same, Google thinks I am interested in buying the same.

This particularly shows that the wrong person was targeted. It is possible they had an awesome offer, but cloud computing is something which I think I never have to buy. The company paid for that to be shown to the right audience, and that didnt happen.

AI can release you from the stress of targeting the right audience. Itll target the right audience for you, and there are minimum possibilities of AI to go wrong. This is the feature that most of us need, as finding the right audience is a great challenge.

Take the phones of two different persons and go to the Amazon or Flipkart app, and you will see the difference.

Different products would be shown on their main page, and this is how people want to experience online shopping. They offer lakhs of products, and no one wants to see what they are not interested in. This is where AI stores what they like and thus show them the related products.

Now, AI is completely changing how people shop online. One of the reasons that people prefer traditional shopping was that they were able to try the clothes at the shop and they were able to see if it suits them or not. Thanks to Augmented Reality, people can now take the trail online.

People can now take a trail of the clothes that they want to buy, and thus this is making their experience more pleasant.

AI is centralized towards creating an awesome customer experience. This helps companies to earn more as customers are willing to pay more for a better customer experience. A simple example is that we pay more when we go to a salon for a haircut, and we pay less to a local barber, and then we even ask for discounts. The willingness to pay is dependent on the experience.

Therefore you should try to create a pleasant customer experience as you can. According to a report by American Express: Customers who have a positive customer experience spend 74% more.

This feature is one that threatens my job. AI can even write content that is plagiarism-free and filled with the right keywords, and thus they can rank on the google pages.

AI can create eye-catching content. But it is hard to create content that does not contain any plagiarism as facts and studies will remain the same, and if someone uses these facts in their content, this will lead to plagiarism. This gave birth to automated journalism. In this, robots will write the content.

The best example is Heliograf of Washington Post, which has written various articles on the Olympics and politics and has also won awards in Artificial Intelligence.

Product tagging and visual search have started taking digital marketing with an impact. Google first founded this, and it was a wow feature. You just have to start your camera and point it to something, and then you can know what it is.

This means that if someone is looking at your product and dont know what it is, they can just start their camera, and they can know the name and the price of the product. Thus, if someone likes your product and wants to buy it, they are just a camera search away.

This makes it easy for people to find your product and your business.

Technology has become so advanced that phones can identify human voices and address their command. This is not unknown to people due to Siri and Alexa, but still, people cannot use it to their advantage.

Whenever I scroll through Instagram, I do come across some post with an amazing song or beat, but I dont know the name of, but I liked the song, and I want to listen to it, but how can I do that?

The simple answer is to use Shazam or ask Siri to identify the song. It is no longer limited to mobiles. You can also use your speaker to do so.

You should understand that voice search is very different from traditional search. SEO for voice search requires a different approach. Here, long-tail keywords can help your SEO.

With the help of AI and good advertisement knowledge, ads can be personalized according to the targeted customer.

Artificial Intelligence can help in business by doing your work in an error-free way. It can help you in cutting down your expenses, and it can perform the work faster. You can use Artificial intelligence as the ultimate weapon that you need for competitive gain.

Karan Vora is an online marketer and avid tech-savvy blogger. He is associated with Capermint Technologies, a creative app and game development company based in Canada. He loves to write about web & app development, AR/VR, artificial Intelligence, UI/UX, digital marketing and much more. Apart from writing, he loves traveling & photography.

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6 Ways to Improve your Business with Artificial Intelligence - ReadWrite

COPAN’s PhenoMATRIX Fuses the Power of Artificial Intelligence and Culture for Highly Sensitive GBS Detection Using Breakthrough Reading Algorithm -…

"COPAN's PhenoMATRIX not only was able to detect more true positive cultures than manual review of digital culture images, but it shows that chromogenic cultures together with artificial intelligence algorithms can detect GBS colonization with the same high sensitivity as molecular detection systems," said COPAN Diagnostics' Scientific Director Dr. Susan Sharp.

The study, which was published on October 21, 2020, evaluated the performance of the PhenoMatrix Chromogenic Detection Module digital imaging software's ability to detect GBS from LIM broth plated on bioMrieux's CHROMID Strepto Battwo clinical laboratories.

After 48 hours of incubation, the sensitivity of COPAN's PhenoMATRIX was similar to the BD MAX GBS molecular test 95.5% to 96.8% respectively and significantly higher than manual at 90.3%.2

Another noteworthy discovery was that COPAN's software never inaccurately called a culture that was determined to be a positive a negative, and it identified an additional eight true positive specimens that were missed by manual reading. This finding establishes that the innovative PhenoMATRIX AI, plus classic culture, is quite the powerful combination at a fraction of the cost of molecular testing.

"COPAN's AI software, along with the use of chromogenic agars has made our decades-old agar culture for the detection of pathogens 'new' again," Sharp added.

PhenoMATRIX is an advanced set of highly sophisticated AI that gives WASPLab users the power to automatically pre-assess and pre-sort culture plates, read, interpret and segregate bacterial cultures. By grouping negative cultures, which are the majority of the cultures screened, staff can quickly review up to 40 plates per computer screen and batch release negative results eliminating the need to review each plate manually saving time and freeing up technicians to focus on more complex tasks.

Contact us for more information about COPAN's state-of-the-art PhenoMATRIX software and how you can add these intelligent algorithms to your WASPLab system.

References: 1. CDC. Group B Strep (GBS) Fast Facts. https://www.cdc.gov/groupbstrep/about/fast-facts.html. Last reviewed June 11, 2020. Accessed October 27, 2020. 2. Baker J, et al.Digital image analysis for the detection of Group BStreptococcusfrom ChromID StreptoB Media using a PhenoMatrix Artificial Intelligence Software Algorithm. J Clin Microbiol. 2020;doi:10.1128/JCM.01902-19

About COPANWith a reputation for innovation, COPAN is the leading manufacturer of collection and transport systems in the world. COPAN's collaborative approach to pre-analytics has resulted in Flocked Swabs, ESwab, UTM Universal Transport Medium, and laboratory automation, WASP and WASPLab. COPAN carries a range of microbial sampling products, inoculation loops, and pipettes. For more information, visitwww.copanusa.com.

SOURCE COPAN Diagnostics, Inc.

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Google collaborates with NOAA to use artificial intelligence for weather forecasting, research | TheHill – The Hill

Google and the National Oceanic and Atmospheric Administration (NOAA) have signed a three-year deal to use the tech giants artificial intelligence and machine learning to enhance the agencys environmental monitoring, weather forecasting and climate research, according to a joint announcement released Tuesday.

Research under the deal initially focused on developing small-scale artificial intelligence and machine learning systems, and based on the results, NOAA and Google Cloud will focus on executing full-scale prototypes the agency could use across its organization.

Strengthening NOAAs data processing through the use of big data, artificial intelligence, machine learning, and other advanced analytical approaches is critical for maintaining and enhancing the performance of our systems in support of public safety and the economy, NOAA acting administrator Neil Jacobs said in the announcement.

I am excited to utilize new authorities granted to NOAA to pursue cutting-edge technologies that will enhance our mission and better protect lives and property, Jacobs added.

Google engineers and data scientists have used artificial intelligence research to develop new methods for understanding and predicting weather.

NOAAs artificial intelligence strategy aims to infuse new technologies and approaches to increase efficiency and skills through partnerships, training and artificial intelligence-related research and development, according to the announcement.

The price of the three-year agreement was not released.

Earlier this month, Google announced a five-year agreement with the Department of Energy. Under the agreement, the DOE is granted access to Google tools, including the tech giants Google Cloud Platform and Google Workspace productivity tools.

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Cooperation on Artificial Intelligence will boost security and prosperity on both sides of the Atlantic – NATO HQ

"There are considerable benefits of setting up a trans-Atlantic digital community cooperating on Artificial Intelligence (AI) and emerging and disruptive technologies, where NATO can play a key role as a facilitator for innovation and exchange", said NATO Deputy Secretary General Mircea Geoan. On Wednesday (28 October 2020) he took part in a high-level virtual discussion on transatlantic cooperation in the era of AI, organised by the Atlantic Council's Future Europe Initiative and GeoTech Center.

Mr. Geoan engaged in this conversation alongside the Chair and Vice Chair of the National Security Commission on Artificial Intelligence (NSCAI), Dr. Eric Schmidt and Secretary Robert O. Work, and the Head of Cabinet of European Commission Executive Vice-President Margrethe Vestager, Ambassador Kim Jrgensen. They discussed what modern technologies mean for European and American defence and security stakeholders, why the United States and the European Union should cooperate on AI, and how best to promote shared values in the field.

"NATO is a natural platform for transatlantic cooperation of AI," the Deputy Secretary General underlined. NATO offers its consultative mechanisms and unique networks for collaboration on defence and security questions. Bringing together Allies and partners, public and private sector, innovators and industry. We have great communities in areas like military capability development, science and technology, standardisation - and of course our Command Structure and military exercises. We also have new cross-cutting policy teams on Innovation Policy, who cover AI, and on Data Policy, he pointed out.

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Artificial Intelligence Initiative: Bank of Thailand – Central Banking

In 2018, the Bank of Thailand began developing new artificial intelligence(AI) and machine learning tools across a number of its core business lines. Natural language processing, which helps institutions analyse unstructured datasets, has been its focus in recent months.

In the past, we typically studied behaviour and culture of the boards of directors of financial institutions through interviews and surveys, which are very qualitative and subjective, says Wanpracha Chaovalitwongse, senior director of the data management and analytics department. The central bank developed an AI system to analyse board meeting minutes of financial institutions. The tool can automatically identify topics of discussion and quantify the participation level and participation mode of each board: enquiring, reporting, commenting and requesting action.

The system can analyse more than 600 meeting minutes equating to more than 30,000 pages of scanned PDF files from 19 financial institutions. Chaovalitwongse says the system has been routinely used to analyse the differences in behaviour of each board member, and cultural differences of the boards among different financial institutions. Such an assessment allows us to assess the regulatory compliance of the board and give recommendations, as part of the ongoing supervision, he says.

One of the central banks biggest AI projects has been the development of an in-house natural language processing AI system to help with the compilation of statistics. The central bank needs to routinely compile various statistics of data from other public or private agencies and share with other government and international agencies, says Chaovalitwongse.

Data from the Government Fiscal Management Information System(GFMIS), maintained by the Comptroller Generals Department, Ministry of Finance, is among the most challenging.

The data stored within the GFMIS requires an expert to manually organise and cleanse the data before it can be formatted and categorised. On average, more than 180,000 government projects take place each year, which the central banks classify based on International Monetary Fund guidelines.

This involved the central bank sorting through unstructured free text written in Thai. As Thai does not have any space for word segmentation, there is no out-of-the-box tool for Thai word segmentation, says Chaovalitwongse. The central bank developed its own system to automate Thai word segmentation, which allows the central bank to classify expenditures in 30 minutes. When performed manually, the data compilation could take up to three days.

Currency management has also benefited from the deployment of AI. In the past, the Bank of Thailand used quality inspection machines to identify defective banknotes. The machine could not identify the root cause and type of defects for proper machine maintenance, explains Chaovalitwongse.

Classified manually, between 100,000 and 150,000 defect classification errors were recorded each year. Since the deployment of a new automated AI system, the number of errors recorded has declined to fewer than 50,000 annually.

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3 ways Artificial Intelligence Will Help IT MSPs Do Better in 2021 – Channel Futures

Artificial intelligence and machine learning can help make ITSM processes more efficient.

CIOs are now using artificial intelligence (AI) and machine learning (ML) technologies to make IT service management processes more efficient.

A typical use case for artificial intelligence in ITSM involves natural language processing (NLP). User requests for IT services are automated using NLP. IT practitioners get a deeper understanding of their processes by applying machine learning (ML) to ITSM data. The natural language processing technology that powers virtual agents is very often integrated with channels that the employees are familiar with. Many organizations integrate virtual agents with chat services like Slack, where employees can directly communicate with the IT service desks.

ITSM systems generate large volumes of data, so applying machine learning to these systems makes sense. The data collected by these systems is large not only in volume but also in detail. All of this data helps us understand existing IT assets and processes, along with information about their ownership.

These insights help IT understand the real priorities of ITSM issues, work proactively instead of reactively, accelerate time to resolution and enhance employee productivity. In the current age of remote work, enhancing employee experience to ensure business continuity is at the top of every CIOs mind, and artificial intelligence will prove to be just the right technology to use to face this new challenge.

Lets look at the three ways artificial intelligence will help IT MSPs to do better in 2021.

Chatbots integrated with an ITSM environment can easily be used to categorize the problem in employee requests. For example, if an organization has integrated Freshservices Virtual Agent with MS Teams, it creates a channel for employees to raise a service request or resolve their issues. The chat interface is a familiar UI for the employees, and the chatbot will identify whether the employee has a service request or an incident to raise using machine learning.

Another important and time-consuming task normally performed by an agent or complex workflows is routing a ticket to the correct support groups. Chatbots will triage the incoming requests or incidents to the right support group, making the process a lot efficient.

The historical ticket data and an extensive ITSM knowledge base will help agents resolve various requests faster. However, this requires the admins/agents to create an extensive knowledge base covering a wide range of requests and incidents. The ability to directly convert a resolution email to a knowledge base article will help build a rich knowledge base repository. When a similar problem arises, AI and machine learning can be used to dig through this repository and present the closest match to resolve the issue faster.

A well-managed repository will also help with incident resolution throughout the solution. AI can provide advice that is as simple as a related or similar incident along with its history, or a solution article with words that match the current incident/request, thereby shortening the time taken to think through the issue from scratch.

Like employee onboarding, many requests to IT demand human staff hours to perform a series of complex tasks to fulfill the requests. Machine learning models watch and learn how humans carry on and execute them to automate them in the future. By recognizing patterns in the request types and execution methods, machine learning-based models make intelligent suggestions for even the most complex IT processes.

Hemalakshmi is a Product Expert with Freshworks. Her responsibility includes educating and helping industry peers and customers on best practices, tips and tricks, quick guides, and solutions around IT Service Management and its various use cases. In her 6+ years of experience in the core SaaS business applications serving as a product expert, Hema has worked with multiple businesses in helping them with their business needs and setting up their service desk solution Freshservice.Follow her onLinkedIn.

This guest blog is part of a Channel Futures sponsorship.

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The Very Human Labor That Powers Artificial Intelligence – The Nation

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In 2015, Caroline Sinders was working as a design researcher at IBM when she began to have questions about how Watson, the companys artificial intelligence system, was being developed. AI systems like Watson must be trained with data setsfor example, given a large batch of confirmed photographs of stop signs from different angles, in different lighting, and of different quality to be able to recognize stop signs on their own. Sinders was curious about these data sets: The process of correctly categorizing millions of data points seemed like a herculean task in its own right; where, exactly, was all this data coming from?Ad Policy

A lot of my coworkers were like, I dont know why youre asking us these questions, were just supposed to build this system out, she recalls.

While Sinderss coworkers may have been able to push the question aside, finding the answer of where the data sets necessary to train artificial intelligence systems come from eventually led her to the world of crowd-working platforms. Amazons Mechanical Turk and other platforms such as Fiverr, Clickworker, Microworker, and Crowdcloud allow employers to offer workers repetitive, task-based assignments at flat rates. Because all the work is digital, workers from around the world perform tasks on these platformsand given that crowd-workers are considered independent contractors, minimum wage laws dont apply.

Artificial intelligence systems, Sinders discovered, still depend on very human grunt work for their raw material. To illustrate the human cost of artificial intelligencethe millions of hours of work that have gone, and continue to go, into making the most profitable AI possibleSinders created the Technically Responsible Knowledge Wage Calculator.Crowdlabor

As its name suggests, the TRK Wage Calculator allows users to calculate earnings for crowd-working assignments. The calculator features three sliders: number of images to label (labeling data is a common task in artificial intelligence development), price per task, and time per task. The results are bleak. According to the calculator, an average assignment, labeling 3,200 images for 32 cents each at a speed of two minutes per image, would yield a worker less than $63 per daywhich, the calculator points out, works out to less than minimum wage in Washington, the state in which Amazon is headquartered.

The TRK Wage Calculator does not capture the full complexity of crowd-working, nor is it intended to. While most workers on Mechanical Turk reside in the United States (there are more than a million workers worldwide), it goes without saying that they arent all found in Washington. The location was selected by Sinders because it is both the state with the highest minimum wage in the United States and home to Amazon. These details contribute to the conception of the TRK Wage Calculator as a mathematical provocation, rather than a genuine toolan artful way of calling out Amazon for allowing the ruthless exploitation of workers, which it could easily prevent by setting parameters for pricing. (Amazon did not respond to multiple requests for comment for this article.)

Sinders created the TRK Wage Calculator as part of her residency with the Mozilla Foundation. The foundation is responsible for the development of the Firefox web browser and, more generally, is dedicated to keeping the Internet open and accessible. Sinderss prompt during her residency was to explore artificial intelligence, which she decided to pursue because of lingering questions from her time at IBM and her own ongoing project, Feminist Data Set, examining how the development of artificial intelligence can integrate feminist values like fair compensation.Current Issue

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Using intersectional feminism as a way to interrogate machine learningthats an interrogation of how you label and frame data, she explains. So then you have to think about labor, right?

For further perspective into the development of artificial intelligence, Sinders joined Mechanical Turk as a worker and interviewed other crowd-workers in the United States and India. (After the United States, India is the second most prevalent nationality of workers on Mechanical Turk.) The experience and interviews revealed how even an apparently fruitful crowd-working assignment can become a morass of additional tasks.

What I realized was that time isnt really listed a lot in the interfaces, but time is a major component of how you do work, Sinders explains.

With crowd-work priced per assignment or per task, the amount of time involved is obscured. A $50 assignment might involve six hours of workor 16 hours of work. The former is one day of work at the federal minimum wage in the United States; the latter is two days of work well below the minimum wage (or one especially hellish day of overtime at the same rate). Even well-meaning employers on crowd-sourcing platforms may underestimate the amount of time necessary to complete their assignments, especially if they lack experience completing the tasks themselves and fail to account for realities like fatigue, to say nothing of break time for meals or bathroom visits. Such genuine misestimation is compounded by outright lowballing, resulting in Mechanical Turk workers earning an estimated $2 per hour on average.

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When you dont think about time, it doesnt account for how you can be paid radically differently, says Sinders. If someone were like, Please label these 1,000 images and heres $50, that may sound really good at firstexcept if you ask how long it takes.

Besides Mechanical Turk, one of the other crowd-working platforms that Sinders focused on when creating the TRK Wage Calculator was CrowdFlower, which was acquired by Appen in 2019. Appen now provides artificial-intelligence-related services to Amazon, Microsoft, Adobe, and other tech companies.

Appen collects and labels images, text, speech, audio, video, and other data used as training data to build and continuously improve artificial intelligence systems, explains Brian Reavey, a director at the company. Our platform allows clients to specify tasks needed for their specific project. For example, a company working on voice commands to improve a vehicles infotainment system might request spoken words or phrases that are commonly used while driving a vehicle in a variety of languages and dialects.

We have over 1 million crowd-workers around the world, says Reavey, and our Crowd Code of Ethics is our commitment to pay fair wages to all members of the crowd.

While Reavey touts Appens code of ethics, the commitment regarding fair pay is vague, stating only that it is the companys goal to pay above minimum wage. Appen says that it tries to comply with local minimum wage standards in the 130-plus countries where it operates by utilizing AI to predict how long specific tasks should takewhich only brings us full circle back to the black box of AI development, and Sinderss first question of where IBMs data sets were coming from. Yet whether Appen is as rigorous in its determination of minimum wage as the TRK Wage Calculator is exactly the sort of question that Sinders hoped to elicit with her project.

It can be used by workers themselves as an advocacy tool, she explains, but I was more interested in trying to have smaller start-ups, research labs, artists, and individuals who use things like Mechanical Turk, Fiverr, and CrowdFlower really understand that when they offer to pay for work, if they dont have an understanding of time and how much that work really costs, they are complicit in underpaying.

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The Very Human Labor That Powers Artificial Intelligence - The Nation

Procore Delivers Artificial Intelligence to Unlock Insights from Construction Data – PRNewswire

Procore CEO and founder, Tooey Courtemanche, said, "With our AI-powered insights and industry benchmark data, Procore users can make better, real-time decisions, improve their construction processes, and mitigate risk. The ways Procore is applying automation and machine learning is making Procore users fundamentally better at their jobs."

Key initiatives and product updates are below.

Acquisition of Avata Intelligence

Procore is committed to investing in next-generation analytics products and approaches that will create new ways of interacting with data. As part of this commitment, Procore acquired Avata Intelligence, an AI firm, and brought world-class AI talent into Procore earlier this year.

This acquisition has expanded Procore's AI functionality and improved processes throughout the construction lifecycle. For example, Procore is further investing in ways to automate repetitive laborious tasks, uncover hidden information, and provide actionable insights to drive better outcomes for its users.

Search Everything from One Place with Procore Search

The documents, photos, and communications that exist within a given project in Procore are a valuable bank of information for project stakeholders. With the new feature Procore Search, Procore has improved how this project information is structured and accessed.

Procore Search offers a single and consistent search experience that uses machine learning to quickly and accurately return search results across an entire project, regardless of what Procore tool is being used when a search is conducted. This search functionality is possible because the Procore platform is built on a singular, integrated system.

"This is a game changer in how we search for and find information throughout the different elements of our project management tools," said Matt Redman, Del Amo Construction. "It brings contextual search to a full project scale, and has allowed our people to find and connect information that would have been extremely difficult to correlate before."

Enhanced search is one more way Procore is redefining the expectations of a modern construction management solution. Procore Search is available to all Procore users.

A Smarter Way to Build Submittals

Procore Submittal Builder automatically generates a submittal register within minutes by scanning every page of a specification book. This form of automation saves Procore customers valuable time as they are no longer required to read and manually create submittals. Procore customers have reported saving 5-7 days of work per project with Submittal Builder, and there is room for automation to further improve the submittal process and save even more time.

Procore is using machine learning to improve submittal recognition on specifications to make the process of creating submittals easier and more efficient for customers. Procore is also applying machine learning models that improve the accuracy and speed at which submittals can be generated. This technology works behind the scenes so customers can spend more time focusing on other critical aspects of a job.

Customized Reporting Capabilities with Procore Analytics

Procore Analytics gives customers an easy way to analyze their data from Procore, as well as data from their integrated tech stack, in one central location. Procore Analytics was created alongside construction professionals, ensuring that its reporting meets the specific needs of the construction industry. Recent additions to Procore Analytics' reporting capabilities include:

Industry Benchmarking

"For years construction companies have lacked meaningful, reliable industry benchmarks against which they can measure their own performance," said Kris Lengieza, Senior Director, Business Development at Procore. "As the industry shifts towards being more insight driven, the importance of external benchmarks is increasing."

Procore is leveraging machine learning to identify objective industry and project level benchmarks for its customers. The insights these benchmarks provide will help customers prioritize their daily activities while optimizing for project success. Procore is continuing to expand its benchmarking capabilities, and invites customers interested to see how their performance stacks up against the industry to request an invitation to join the benchmarking initiative.

Find out more about how Procore is advancing the use of AI in construction, while providing greater access to insights from construction data by attending Groundbreak on Oct 27-28, 2020.

About ProcoreProcore is a leading provider of construction management software. Over 1 million projects and more than $1 trillion USD in construction volume have run on Procore's platform. Our platform connects every project stakeholder to solutions we've built specifically for the construction industryfor the owner, the general contractor, and the specialty contractor. Procore's App Marketplace has a multitude of partner solutions that integrate seamlessly with our platform, giving construction professionals the freedom to connect with what works best for them. Headquartered in Carpinteria, California, Procore has offices around the globe. Learn more at Procore.com.

CONTACT: [emailprotected]

SOURCE Procore Technologies, Inc.

http://www.procore.com

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Procore Delivers Artificial Intelligence to Unlock Insights from Construction Data - PRNewswire